Update app.py

app.py

@@ -1,8 +1,8 @@
 import gradio as gr
 import json, os, sys, glob, shutil, subprocess
 from PIL import Image
-
-#os.system("git clone https://github.com/sunset1995/HorizonNet.git /tmp/HorizonNet")
+if not os.path.isdir('/tmp/HorizonNet'):
+    os.system("git clone https://github.com/sunset1995/HorizonNet.git /tmp/HorizonNet")
 sys.path.insert(0, "/tmp/HorizonNet")
 
 from huggingface_hub import hf_hub_download
@@ -20,45 +20,53 @@ def run(cmd, cwd="/tmp/HorizonNet"):
     return result.returncode, log
 
 def predict(image):
-    for d in ["/tmp/hn_input", "/tmp/hn_pre", "/tmp/hn_out"]:
-        shutil.rmtree(d, ignore_errors=True)
-        os.makedirs(d)
+    try:
+        for d in ["/tmp/hn_input", "/tmp/hn_pre", "/tmp/hn_out"]:
+            shutil.rmtree(d, ignore_errors=True)
+            os.makedirs(d)
+
+        img_path = "/tmp/hn_input/room.png"
+        image.convert("RGB").resize((1024, 512)).save(img_path)
+        print("Image saved to", img_path)
 
-    img_path = "/tmp/hn_input/room.png"
-    image.convert("RGB").resize((1024, 512)).save(img_path)
+        # Step 1: preprocess
+        code, log = run([
+            "python", "preprocess.py",
+            "--img_glob", img_path,
+            "--output_dir", "/tmp/hn_pre"
+        ])
 
-    # Step 1: preprocess
-    code, log = run([
-        "python", "preprocess.py",
-        "--img_glob", img_path,
-        "--output_dir", "/tmp/hn_pre"
-    ])
+        aligned = glob.glob("/tmp/hn_pre/*_aligned_rgb.png")
+        if not aligned:
+            return json.dumps({"error": "Preprocessing failed", "code": code, "log": log[-1000:]})
 
-    aligned = glob.glob("/tmp/hn_pre/*_aligned_rgb.png")
-    if not aligned:
-        return json.dumps({"error": "Preprocessing failed", "code": code, "log": log[-1000:]})
+        aligned_path = aligned[0]
+        print("Aligned image:", aligned_path)
 
-    aligned_path = aligned[0]
-    print("Aligned image:", aligned_path)
+        # Step 2: inference
+        code, log = run([
+            "python", "inference.py",
+            "--pth", CKPT,
+            "--img_glob", aligned_path,
+            "--output_dir", "/tmp/hn_out",
+            "--no_cuda"
+        ])
 
-    # Step 2: inference
-    code, log = run([
-        "python", "inference.py",
-        "--pth", CKPT,
-        "--img_glob", aligned_path,
-        "--output_dir", "/tmp/hn_out",
-        "--no_cuda"
-    ])
+        out_jsons = glob.glob("/tmp/hn_out/*.json")
+        if not out_jsons:
+            return json.dumps({"error": "Inference failed", "code": code, "log": log[-1000:]})
 
-    out_jsons = glob.glob("/tmp/hn_out/*.json")
-    if not out_jsons:
-        return json.dumps({"error": "Inference failed", "code": code, "log": log[-1000:]})
+        with open(out_jsons[0]) as f:
+            result = json.load(f)
 
-    with open(out_jsons[0]) as f:
-        result = json.load(f)
+        print("Result:", result)
+        return json.dumps(result)
 
-    print("Result:", result)
-    return json.dumps(result)
+    except Exception as e:
+        import traceback
+        tb = traceback.format_exc()
+        print("=== EXCEPTION ===\n", tb)
+        return json.dumps({"error": str(e), "traceback": tb})
 
 demo = gr.Interface(
     fn=predict,